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Paper Citation Record · LEDGER

Can Large Language Models Generalize Procedures Across Representations?

As of 7 August 2026, this Paper Citation Record lists 83 of 83 outbound references and 0 inbound Pith citation observations for arXiv:2602.03542.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2602.03542 v2

Coverage vector

measured 83 of 83 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T05:01:02.074739Z

measured 83 of 83 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

83 of 83 outbound references displayed

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External citation measurements

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Outbound references

Observation 4e802f0f-1cd3-4325-987c-7299da77e1bd · outbound

This paper cites and Thompson, V.

Can Large Language Models Generalize Procedures Across Representations? and Thompson, V

Reference 1

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Observation bc52f0c0-0f69-4056-bdae-4ebe1b37b82f · outbound

This paper cites To Code, or Not To Code? Exploring Impact of Code in Pre-training.

Can Large Language Models Generalize Procedures Across Representations? To Code, or Not To Code? Exploring Impact of Code in Pre-training

Reference 2

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Observation b5bc6d75-5b51-4498-b005-0349469370e0 · outbound

This paper cites D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al.

Can Large Language Models Generalize Procedures Across Representations? D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al

Reference 3

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Observation 4e8230ee-49a1-412b-a77b-83ff87caa35c · outbound

This paper cites H., Baker, B., Gao, L., Aschenbrenner, L., Chen, Y., Ecoffet, A., Joglekar, M., Leike, J., et al.

Can Large Language Models Generalize Procedures Across Representations? H., Baker, B., Gao, L., Aschenbrenner, L., Chen, Y., Ecoffet, A., Joglekar, M., Leike, J., et al

Reference 4

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Observation f6e644ce-2788-4365-a95b-8cb70593254d · outbound

This paper cites Plan recognition in natural language dialogue.

Can Large Language Models Generalize Procedures Across Representations? Plan recognition in natural language dialogue

Reference 5

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Observation 58b6cc47-99d5-4b7d-8b2d-bff526962c8c · outbound

This paper cites Logic distillation: Learning from code function by function for planning and decision-making.

Can Large Language Models Generalize Procedures Across Representations? Logic distillation: Learning from code function by function for planning and decision-making

Reference 6

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Observation 311ce86f-db54-471f-adf4-91feba723412 · outbound

This paper cites SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training.

Can Large Language Models Generalize Procedures Across Representations? SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training

Reference 7

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Observation 35bac16c-3b90-4390-9ede-b80d7a8f0ad2 · outbound

This paper cites Leveraging procedural generation to benchmark reinforcement learning.

Can Large Language Models Generalize Procedures Across Representations? Leveraging procedural generation to benchmark reinforcement learning

Reference 8

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Observation 2c37d17d-e203-4e76-b44f-3e386e945445 · outbound

This paper cites Understanding the generative capacity of analogies as a tool for explanation.

Can Large Language Models Generalize Procedures Across Representations? Understanding the generative capacity of analogies as a tool for explanation

Reference 9

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Observation 414976e1-bcab-48a0-85a7-ee0fb82eeeb0 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Can Large Language Models Generalize Procedures Across Representations? DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 10

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Observation 2c611f38-6930-4290-82ce-33eeb0ac4854 · outbound

This paper cites TCP : a benchmark for temporal constraint-based planning.

Can Large Language Models Generalize Procedures Across Representations? TCP : a benchmark for temporal constraint-based planning

Reference 11

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Observation 03e56ed6-9bb8-4e83-acdf-9a007d6ab7e4 · outbound

This paper cites A., Hummel, J.

Can Large Language Models Generalize Procedures Across Representations? A., Hummel, J

Reference 12

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Observation c3262921-59c8-4cd8-9b51-998ac3885535 · outbound

This paper cites A., Puebla, G., Martin, A.

Can Large Language Models Generalize Procedures Across Representations? A., Puebla, G., Martin, A

Reference 13

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Observation 2215b900-92ad-413a-a8ad-17d99b9063da · outbound

This paper cites The llama 3 herd of models.

Can Large Language Models Generalize Procedures Across Representations? The llama 3 herd of models

Reference 14

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Observation 0b17d7fe-689d-4643-a921-11032809a354 · outbound

This paper cites D., and Gentner, D.

Can Large Language Models Generalize Procedures Across Representations? D., and Gentner, D

Reference 15

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Observation 134b20d6-b7de-48d7-8c02-f130debe14f3 · outbound

This paper cites and Sims, C.

Can Large Language Models Generalize Procedures Across Representations? and Sims, C

Reference 16

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Observation f9aaa4cc-86ec-4f0a-bedb-06b648e01521 · outbound

This paper cites Pal: Program-aided language models.

Can Large Language Models Generalize Procedures Across Representations? Pal: Program-aided language models

Reference 17

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Observation 8d696369-4c3b-4c22-a5b5-a382d8377201 · outbound

This paper cites Generative analogies as mental models.

Can Large Language Models Generalize Procedures Across Representations? Generative analogies as mental models

Reference 18

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Observation cadd2f97-77e4-4a59-9c0c-c95135430338 · outbound

This paper cites Structure-mapping: A theoretical framework for analogy.

Can Large Language Models Generalize Procedures Across Representations? Structure-mapping: A theoretical framework for analogy

Reference 19

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Observation 2241a15f-2229-4eb1-9b3b-82dc8db9c66a · outbound

This paper cites L., Callaway, F., Chang, M.

Can Large Language Models Generalize Procedures Across Representations? L., Callaway, F., Chang, M

Reference 20

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Observation 24031c82-e2a3-44ef-aed9-1dd8a94ec718 · outbound

This paper cites Mini LLM : Knowledge distillation of large language models.

Can Large Language Models Generalize Procedures Across Representations? Mini LLM : Knowledge distillation of large language models

Reference 21

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Observation c846cbac-5847-42bd-b970-7d095c4c2a59 · outbound

This paper cites The unreasonable effectiveness of easy training data for hard tasks.

Can Large Language Models Generalize Procedures Across Representations? The unreasonable effectiveness of easy training data for hard tasks

Reference 22

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Observation eb5f1ad3-55d4-4e41-a093-4de7034ffb29 · outbound

This paper cites Measuring mathematical problem solving with the MATH dataset.

Can Large Language Models Generalize Procedures Across Representations? Measuring mathematical problem solving with the MATH dataset

Reference 23

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Observation c45b5e82-6034-486a-bfe5-ee1a7806228f · outbound

This paper cites Derivational Morphology Reveals Analogical Generalization in Large Language Models.

Can Large Language Models Generalize Procedures Across Representations? Derivational Morphology Reveals Analogical Generalization in Large Language Models

Reference 24

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Observation b9680774-748d-4a6f-bbd0-1814594c9893 · outbound

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Can Large Language Models Generalize Procedures Across Representations? Unresolved cited work

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Observation 3a6e38dd-55ea-43da-825f-e10b3a2c4a23 · outbound

This paper cites OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF Framework.

Can Large Language Models Generalize Procedures Across Representations? OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF Framework

Reference 26

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Observation 6aa2461e-1db3-49c5-8729-1051d4f4fc0e · outbound

This paper cites Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model.

Can Large Language Models Generalize Procedures Across Representations? Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model

Reference 27

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Observation c76fbff9-3b37-4f77-8753-3160923dbc40 · outbound

This paper cites Loong: Synthesize long chain-of-thoughts at scale through verifiers.

Can Large Language Models Generalize Procedures Across Representations? Loong: Synthesize long chain-of-thoughts at scale through verifiers

Reference 28

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Observation 0a0fb7f2-9cc8-4dbe-b9cf-f855b493b700 · outbound

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Can Large Language Models Generalize Procedures Across Representations? Unresolved cited work

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Observation 829a7b52-5cb7-4eeb-a162-444585bc8d93 · outbound

This paper cites Code Pretraining Improves Entity Tracking Abilities of Language Models.

Can Large Language Models Generalize Procedures Across Representations? Code Pretraining Improves Entity Tracking Abilities of Language Models

Reference 30

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Observation 63f0f58a-793a-4938-99da-4e0ad11e0d90 · outbound

This paper cites S., Reid, M., Matsuo, Y., and Iwasawa, Y.

Can Large Language Models Generalize Procedures Across Representations? S., Reid, M., Matsuo, Y., and Iwasawa, Y

Reference 31

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Observation 89827ef2-c89a-444e-a2af-65af914955e0 · outbound

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Can Large Language Models Generalize Procedures Across Representations? M., and Raghunathan, A

Reference 32

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Observation 3ff41184-b29d-4e3b-ab38-22a343d343c8 · outbound

This paper cites Code Simulation Challenges for Large Language Models.

Can Large Language Models Generalize Procedures Across Representations? Code Simulation Challenges for Large Language Models

Reference 33

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Observation c0ff19a9-f360-42b1-a935-dfc230cb54f7 · outbound

This paper cites Code Simulation as a Proxy for High-order Tasks in Large Language Models.

Can Large Language Models Generalize Procedures Across Representations? Code Simulation as a Proxy for High-order Tasks in Large Language Models

Reference 34

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Observation 0eecf513-f224-45a9-b028-defb13cefe26 · outbound

This paper cites Tulu 3: Pushing Frontiers in Open Language Model Post-Training.

Can Large Language Models Generalize Procedures Across Representations? Tulu 3: Pushing Frontiers in Open Language Model Post-Training

Reference 35

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Observation 303eb591-5af0-4ac1-a58a-ef15176d6704 · outbound

This paper cites Why and how to learn why: Analysis-based generalization of procedures.

Can Large Language Models Generalize Procedures Across Representations? Why and how to learn why: Analysis-based generalization of procedures

Reference 36

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Observation a0322c30-3942-409f-a309-44e1e89970ea · outbound

This paper cites Evaluating the Robustness of Analogical Reasoning in Large Language Models.

Can Large Language Models Generalize Procedures Across Representations? Evaluating the Robustness of Analogical Reasoning in Large Language Models

Reference 37

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Observation 2e28df12-16bd-41bf-b357-ab7419e92066 · outbound

This paper cites CodeI/O: Condensing Reasoning Patterns via Code Input-Output Prediction.

Can Large Language Models Generalize Procedures Across Representations? CodeI/O: Condensing Reasoning Patterns via Code Input-Output Prediction

Reference 38

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Observation 46816586-694b-4e16-a234-a17ccd2a6792 · outbound

This paper cites Graph-enhanced Large Language Models in Asynchronous Plan Reasoning.

Can Large Language Models Generalize Procedures Across Representations? Graph-enhanced Large Language Models in Asynchronous Plan Reasoning

Reference 39

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source=arxiv_source observed=2026-08-03T05:00:57.768657Z digest=sha256:01512b8dfdae999bfab09453926349e12a16f9103b16dd551e6578e4d93f56f6

Observation 9ec81c3e-c9af-4f29-9aaf-a04f340e6995 · outbound

This paper cites Assessing Dialect Fairness and Robustness of Large Language Models in Reasoning Tasks.

Can Large Language Models Generalize Procedures Across Representations? Assessing Dialect Fairness and Robustness of Large Language Models in Reasoning Tasks

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source=arxiv_source observed=2026-08-03T05:00:57.834547Z digest=sha256:80781bb3803c84da5d22418aa8d7da41f858ae824b9b0524bd58ea314c76a399

Observation 81f8c7eb-6b87-4f8d-8b24-8236f0c58744 · outbound

This paper cites The centrality of language in human cognition.

Can Large Language Models Generalize Procedures Across Representations? The centrality of language in human cognition

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source=arxiv_source observed=2026-08-03T05:00:57.904281Z digest=sha256:ef4320ec1ce50bff71b39b5a7d498299bfdd595273bf58e5c9d93319dbd7464e

Observation fdaf3e6a-8f9e-4a97-aec3-16b68e92469e · outbound

This paper cites At which training stage does code data help LLM s reasoning? In The Twelfth International Conference on Learning Representations, 2024.

Can Large Language Models Generalize Procedures Across Representations? At which training stage does code data help LLM s reasoning? In The Twelfth International Conference on Learning Representations, 2024

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source=arxiv_source observed=2026-08-03T05:00:58.011225Z digest=sha256:41e39a5d8668e927bc6e4a6018a8125718a2a3848614b292d93b20d0230e89d5

Observation befc1ae5-a0c9-4598-9106-ab9ae78531b3 · outbound

This paper cites Note on the sampling error of the difference between correlated proportions or percentages.

Can Large Language Models Generalize Procedures Across Representations? Note on the sampling error of the difference between correlated proportions or percentages

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source=arxiv_source observed=2026-08-03T05:00:58.112172Z digest=sha256:4f2a9dbbb5246d3bcffcee3f1a6ff7cc3ac5f5bb493fd91c091de873539a456e

Observation f20af8f7-7b77-4d5b-9a4a-388ef3794d78 · outbound

This paper cites Linguistic regularities in continuous space word representations.

Can Large Language Models Generalize Procedures Across Representations? Linguistic regularities in continuous space word representations

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source=arxiv_source observed=2026-08-03T05:00:58.183627Z digest=sha256:bba6ea049a021afb91c1a98287d16c18e8336df1151c1d998a2ec3fb66ab7e59

Observation de6e0a06-5604-4d58-aa14-4c6cc7eca472 · outbound

This paper cites Large Language Models as General Pattern Machines.

Can Large Language Models Generalize Procedures Across Representations? Large Language Models as General Pattern Machines

Reference 45

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source=arxiv_source observed=2026-08-03T05:00:58.255516Z digest=sha256:a1c6069aacd882285e354d95f9c5c254178e2da0e835b5d3b21d828e2fe419f9

Observation 0c7a0887-027e-4e84-9afc-1a5cc3ed8f22 · outbound

This paper cites M., Keller, R.

Can Large Language Models Generalize Procedures Across Representations? M., Keller, R

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source=arxiv_source observed=2026-08-03T05:00:58.311397Z digest=sha256:174e611ce4bbb21753d79f578b4a1c9155463ec924c8db403cf068041f7fd6a3

Observation 17bf605a-5121-4bb0-b811-38cf3a7a8126 · outbound

This paper cites an unresolved cited work.

Can Large Language Models Generalize Procedures Across Representations? Unresolved cited work

Reference 47

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source=arxiv_source observed=2026-08-03T05:00:58.386480Z digest=sha256:1797c92261cd766e95ca1813bb163b8333b67bb59d81e9e486ce7e3722f9bf71

Observation b30653f2-6725-4f31-a37a-ad1b3270fb19 · outbound

This paper cites Semantic structure-mapping in llm and human analogical reasoning.

Can Large Language Models Generalize Procedures Across Representations? Semantic structure-mapping in llm and human analogical reasoning

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source=arxiv_source observed=2026-08-03T05:00:58.451730Z digest=sha256:d4dd127e4e77da1707c4ee1f1e6c5aa91e71a484efb4692c2e7667f2166a919c

Observation 4964229a-45e5-4d1c-92e7-dd0fb6316ef8 · outbound

This paper cites 2 OLMo 2 Furious.

Can Large Language Models Generalize Procedures Across Representations? 2 OLMo 2 Furious

Reference 49

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source=arxiv_source observed=2026-08-03T05:00:58.527963Z digest=sha256:6dbb2049b272aeebe05aa6474a9ed3d017b5ede23ef098bc8b30349c6ca2d662

Observation 2f4cc66e-e539-44b5-9874-9109cfb6dfe6 · outbound

This paper cites Training language models to follow instructions with human feedback.

Can Large Language Models Generalize Procedures Across Representations? Training language models to follow instructions with human feedback

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source=arxiv_source observed=2026-08-03T05:00:58.603897Z digest=sha256:67ac74c1aa424cbe754f9db7b439051c3c037789b6a262e25098383c7d27ec1e

Observation 45db572e-5bc1-40dd-a8e4-4e8702c15d06 · outbound

This paper cites and van der Plas, L.

Can Large Language Models Generalize Procedures Across Representations? and van der Plas, L

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source=arxiv_source observed=2026-08-03T05:00:58.670916Z digest=sha256:0cdef660df79a756727010712374f366c6b15b79fe7afaafcc3713d154cae8b4

Observation 557a7c30-46a9-49f0-b5e6-8b99fbdb41f4 · outbound

This paper cites How does code pretraining affect language model task performance? In The 7th BlackboxNLP Workshop, 2024.

Can Large Language Models Generalize Procedures Across Representations? How does code pretraining affect language model task performance? In The 7th BlackboxNLP Workshop, 2024

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source=arxiv_source observed=2026-08-03T05:00:58.773911Z digest=sha256:e15960e520371fcbf1588c835d7ad6d2bc26e059959fe92bde8952945a5ab0ed

Observation 4fa1e4a2-b4d9-4ffb-b79f-4ce681e47221 · outbound

This paper cites Relevant or Random: Can LLMs Truly Perform Analogical Reasoning?.

Can Large Language Models Generalize Procedures Across Representations? Relevant or Random: Can LLMs Truly Perform Analogical Reasoning?

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source=arxiv_source observed=2026-08-03T05:00:58.853348Z digest=sha256:b52d6b7e86e715c7b6f24629f30cad1676e04c8c54dc5fe047b0e178533f7a77

Observation e6c2549b-1146-43f2-af64-fad26d71bf6d · outbound

This paper cites Procedural Knowledge in Pretraining Drives Reasoning in Large Language Models.

Can Large Language Models Generalize Procedures Across Representations? Procedural Knowledge in Pretraining Drives Reasoning in Large Language Models

Reference 54

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source=arxiv_source observed=2026-08-03T05:00:58.901487Z digest=sha256:0f783699695c267e724b7177f3d91817310d8227f892ce43e59470fdbba61dd8

Observation b77a58e0-3134-4cf9-a55a-03842b9835f6 · outbound

This paper cites and Wefald, E.

Can Large Language Models Generalize Procedures Across Representations? and Wefald, E

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source=arxiv_source observed=2026-08-03T05:00:58.973491Z digest=sha256:25aa956d585c70b256e7043ccac543b974769eb89fad8452548f5fc80b2073fc

Observation 932bc603-5842-42a5-931c-faad9383dad5 · outbound

This paper cites Can you learn an algorithm? generalizing from easy to hard problems with recurrent networks.

Can Large Language Models Generalize Procedures Across Representations? Can you learn an algorithm? generalizing from easy to hard problems with recurrent networks

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source=arxiv_source observed=2026-08-03T05:00:59.065363Z digest=sha256:7658546c829e19545150f03f34c5a0477bffcc4713e2792a568434287da35141

Observation c2a6b4f8-32b5-4239-866c-061e0cf7c473 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

Can Large Language Models Generalize Procedures Across Representations? DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

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source=arxiv_source observed=2026-08-03T05:00:59.215019Z digest=sha256:4488dc60f2c4f2197529c8b87eba0f33ab32ae868119cb99afaf8fa08d1c00ff

Observation 9719b77b-bda9-4f68-a5bb-c8ccf3349162 · outbound

This paper cites an unresolved cited work.

Can Large Language Models Generalize Procedures Across Representations? Unresolved cited work

Reference 58

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source=arxiv_source observed=2026-08-03T05:00:59.389751Z digest=sha256:3480a347a2f589c2bd7c27b126bfcdf408a310f2915fd9ed0f77ed850d79ce3b

Observation 13f5148d-59cd-429f-a45d-a128de7b6a74 · outbound

This paper cites J., Mehlhorn, K., and Borgwardt, K.

Can Large Language Models Generalize Procedures Across Representations? J., Mehlhorn, K., and Borgwardt, K

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source=arxiv_source observed=2026-08-03T05:00:59.550489Z digest=sha256:7daee5ba080211630f9231e22b38f9ba4fa5264426da13616d26932cd25da093

Observation a0d4958b-a9be-4ce4-a963-8ef10f33cb8f · outbound

This paper cites Parallelparc: A scalable pipeline for generating natural-language analogies.

Can Large Language Models Generalize Procedures Across Representations? Parallelparc: A scalable pipeline for generating natural-language analogies

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source=arxiv_source observed=2026-08-03T05:00:59.666616Z digest=sha256:1fe5274a70a8f12aa0b76f50ba644ad74782dc2ad3bdcf6ef97a7e17b7e6e97d

Observation 8d6ac151-306a-45a3-9a3c-b4d93e3ac4f7 · outbound

This paper cites Easy-to-hard generalization: Scalable alignment beyond human supervision.

Can Large Language Models Generalize Procedures Across Representations? Easy-to-hard generalization: Scalable alignment beyond human supervision

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source=arxiv_source observed=2026-08-03T05:00:59.716142Z digest=sha256:df0f2176a810dc475dec84e1b16a3d96c4455c05bca24ef4da1319220f02b25b

Observation 80e844a3-6b5d-4b27-aa76-78ef7dad9c49 · outbound

This paper cites Qwq-32b: Embracing the power of reinforcement learning, March 2025.

Can Large Language Models Generalize Procedures Across Representations? Qwq-32b: Embracing the power of reinforcement learning, March 2025

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source=arxiv_source observed=2026-08-03T05:00:59.837632Z digest=sha256:3cd9c743a0c408d625a3bdc0bcd3e34fc9918885b28e90aaf90fb313a7ece257

Observation ff6989b1-97a3-4d76-994a-0bca05fda44a · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Can Large Language Models Generalize Procedures Across Representations? LLaMA: Open and Efficient Foundation Language Models

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source=arxiv_source observed=2026-08-03T05:00:59.901423Z digest=sha256:920690c3cc576fe153714a1da645dd616f797c14961662e213cd69f1e40dfad1

Observation 63c00136-b579-4749-83e1-a1ff1faf3a12 · outbound

This paper cites and Kahneman, D.

Can Large Language Models Generalize Procedures Across Representations? and Kahneman, D

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source=arxiv_source observed=2026-08-03T05:01:00.062684Z digest=sha256:528a4bd644cc6bf089711d90f2f1a07d92d1866ea333e8b0afaa6154f1259d9f

Observation 7ed2bc63-ecd0-432a-aa0d-2dd3acdd9b6e · outbound

This paper cites Can language models solve graph problems in natural language? Advances in Neural Information Processing Systems, 36: 0 30840--30861, 2023.

Can Large Language Models Generalize Procedures Across Representations? Can language models solve graph problems in natural language? Advances in Neural Information Processing Systems, 36: 0 30840--30861, 2023

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source=arxiv_source observed=2026-08-03T05:01:00.197988Z digest=sha256:923b1d4d3aab8edbc6d4a0c3ac3972acadd0d06d8310daf896b733cc2bad6af6

Observation bca20ffd-fd5b-4a08-84b9-609ef7f2a36e · outbound

This paper cites R., Zhang, S., Sun, Y., and Wang, W.

Can Large Language Models Generalize Procedures Across Representations? R., Zhang, S., Sun, Y., and Wang, W

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source=arxiv_source observed=2026-08-03T05:01:00.259804Z digest=sha256:ea23c0170e7c771d19a2eb1c8dfff5786d79ee30f8bfd96097e5f0c6da9dddc7

Observation 6cbde601-245b-4ad0-bf2a-1a246e864429 · outbound

This paper cites P lan G en LLM s: A modern survey of LLM planning capabilities.

Can Large Language Models Generalize Procedures Across Representations? P lan G en LLM s: A modern survey of LLM planning capabilities

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source=arxiv_source observed=2026-08-03T05:01:00.385498Z digest=sha256:56d42198f50a1b350cc9ed629d0941677bc6cae0a2856167adf47bf6cb0993e3

Observation db7b4def-c130-4aec-b666-d31d4d076a57 · outbound

This paper cites W., Lester, B., Du, N., Dai, A.

Can Large Language Models Generalize Procedures Across Representations? W., Lester, B., Du, N., Dai, A

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source=arxiv_source observed=2026-08-03T05:01:00.464205Z digest=sha256:2383a7b9a1d46d9f979fc2165445527defe6b72c52b2b1497d41c3a61a9c016f

Observation fd6ff650-ee25-4100-b37f-2110647441e5 · outbound

This paper cites V., Zhou, D., et al.

Can Large Language Models Generalize Procedures Across Representations? V., Zhou, D., et al

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source=arxiv_source observed=2026-08-03T05:01:00.549514Z digest=sha256:ac23123169a03c38746bf9ea73b6dd6a3047d9bcd0f7b090f89123b1e943039d

Observation 7759d371-465d-42e6-a4e0-5715fa22c1b2 · outbound

This paper cites Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Thought.

Can Large Language Models Generalize Procedures Across Representations? Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Thought

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source=arxiv_source observed=2026-08-03T05:01:00.667656Z digest=sha256:c47d18711ce829c33a78a48b1ecb17d243246d062276e8ff895942b6c8b52801

Observation c722c860-edd2-47a5-9682-b78f65bef26e · outbound

This paper cites Qwen2.5 Technical Report.

Can Large Language Models Generalize Procedures Across Representations? Qwen2.5 Technical Report

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source=arxiv_source observed=2026-08-03T05:01:00.767006Z digest=sha256:42ff5d22039d41bb7dad4eea984b9fd01c2a428ac8799e6cdaf27d5f4a717762

Observation 8ebcf2b2-5941-4044-ba4e-cd7396d2d9eb · outbound

This paper cites Emergent Symbolic Mechanisms Support Abstract Reasoning in Large Language Models.

Can Large Language Models Generalize Procedures Across Representations? Emergent Symbolic Mechanisms Support Abstract Reasoning in Large Language Models

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source=arxiv_source observed=2026-08-03T05:01:00.824842Z digest=sha256:fcc48158b9dc42b3ef8e04b58f40c2b5ebba27a65975294534691f6f287e2855

Observation 2bf401cb-e5f9-4488-a572-e38751a15031 · outbound

This paper cites Large Language Models as Analogical Reasoners.

Can Large Language Models Generalize Procedures Across Representations? Large Language Models as Analogical Reasoners

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source=arxiv_source observed=2026-08-03T05:01:00.939052Z digest=sha256:c0736d66cb96783364d4feb108a29e555a81b8bc08ff8410b4663aa8019626e2

Observation 1207f16d-271e-48fc-b97f-684df036e08c · outbound

This paper cites Language is all a graph needs.

Can Large Language Models Generalize Procedures Across Representations? Language is all a graph needs

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source=arxiv_source observed=2026-08-03T05:01:01.092374Z digest=sha256:d8bcd07564efa6d47ea67155fc6587764189cfeb8a939dc2ed2c76faf2963c33

Observation da38b4fb-41b9-4c62-9380-0b0d9c8ef3c1 · outbound

This paper cites LIMO: Less is More for Reasoning.

Can Large Language Models Generalize Procedures Across Representations? LIMO: Less is More for Reasoning

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source=arxiv_source observed=2026-08-03T05:01:01.214340Z digest=sha256:ed81eddc7f0948110634d3915f76e97f3082cd5def194a6b0a65b7074bc5256b

Observation a32d43bc-3e65-454c-a438-c08feae9527d · outbound

This paper cites Thought Propagation: An Analogical Approach to Complex Reasoning with Large Language Models.

Can Large Language Models Generalize Procedures Across Representations? Thought Propagation: An Analogical Approach to Complex Reasoning with Large Language Models

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source=arxiv_source observed=2026-08-03T05:01:01.265276Z digest=sha256:00a0885d7afc55e326a7fe0fbc4b257aa20c7b7cba9ef9081a737762b7a6c25b

Observation 0ff85755-ba1c-476f-83f7-f37e065ba225 · outbound

This paper cites Beneath surface similarity: Large language models make reasonable scientific analogies after structure abduction.

Can Large Language Models Generalize Procedures Across Representations? Beneath surface similarity: Large language models make reasonable scientific analogies after structure abduction

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source=arxiv_source observed=2026-08-03T05:01:01.348392Z digest=sha256:5d80cc0fd01a72df8d1126a3d4fb8da1b707630b25fef779968977b11b2bcd7d

Observation 56fd6eb6-582d-4d1c-8948-0105e1e653b9 · outbound

This paper cites ANALOGYKB: Unlocking Analogical Reasoning of Language Models with A Million-scale Knowledge Base.

Can Large Language Models Generalize Procedures Across Representations? ANALOGYKB: Unlocking Analogical Reasoning of Language Models with A Million-scale Knowledge Base

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source=arxiv_source observed=2026-08-03T05:01:01.514462Z digest=sha256:601af8c97890498b0f68cbb69e4c3e449cdc30fbc58dd5f9eec63e29c6686f2d

Observation c2661d35-18e7-448c-90a3-4c6d7a100a85 · outbound

This paper cites Star: Bootstrapping reasoning with reasoning.

Can Large Language Models Generalize Procedures Across Representations? Star: Bootstrapping reasoning with reasoning

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-03T05:01:01.591690Z digest=sha256:02cfa68965dc13e2be66c1440a9eb5f22e3bffdb4f001ef635309dc843efad24

Observation 01f8a538-9409-4d33-a535-280e4328193f · outbound

This paper cites Z., Ye, X., Yang, X., Chen, L., Wang, W.

Can Large Language Models Generalize Procedures Across Representations? Z., Ye, X., Yang, X., Chen, L., Wang, W

Reference 80

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no resolver link, observed 2026-08-03T05:01:01.734546Z

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source=arxiv_source observed=2026-08-03T05:01:01.734546Z digest=sha256:b73e2bfc9377482f1b3d8f6939f994f2ed86aaf2ba93076aadc334b5a146d9ad

Observation ff67ff8d-5bad-406f-bd3c-e20120badc88 · outbound

This paper cites Can LLM Graph Reasoning Generalize beyond Pattern Memorization?.

Can Large Language Models Generalize Procedures Across Representations? Can LLM Graph Reasoning Generalize beyond Pattern Memorization?

Reference 81

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no resolver link, observed 2026-08-03T05:01:01.836783Z

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source=arxiv_source observed=2026-08-03T05:01:01.836783Z digest=sha256:b771147fa4a8cd70447f92f3f169b25afa8a319b6a2e69e2678ec02f4370cca0

Observation 3bb941f2-832f-407a-8aec-c29ab57d86f4 · outbound

This paper cites LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models.

Can Large Language Models Generalize Procedures Across Representations? LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models

Reference 82

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no resolver link, observed 2026-08-03T05:01:01.970473Z

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source=arxiv_source observed=2026-08-03T05:01:01.970473Z digest=sha256:0c9a241a5557e90ea96bfe35e5c13b10c1a023346afead6561b246850c14ee74

Observation e61c3c37-755c-408a-aa84-f84cfc9b102a · outbound

This paper cites write newline.

Can Large Language Models Generalize Procedures Across Representations? write newline

Reference 83

Resolution
unresolved
no resolver link, observed 2026-08-03T05:01:02.074739Z

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source=arxiv_source observed=2026-08-03T05:01:02.074739Z digest=sha256:0c0ddfa0fe609f31ae877a76e7b35fc715ab5b0d50e49d05730e764e5c085a57

Pith citing papers

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